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    Journal of Cheminformatics
  • Publication Date:
    May 2014
  • Reference:
    Journal of Cheminformatics 2014, 6(21)
  • DOI:
    10.1186/1758-2946-6-21
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  • Publication Type:
    Paper
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Self organising hypothesis networks: a new approach for representing and structuring SAR knowledge

Hanser T; Barber CG; Rosser E; Vessey J; Webb S; Werner S;

Combining different sources of knowledge to build improved structure activity relationship models is not easy owing to the variety of knowledge formats and the absence of a common framework to interoperate between learning techniques. Most of the current approaches address this problem by using consensus models that operate at the prediction level. We explore the possibility to directly combine these sources at the knowledge level, with the aim to harvest potentially increased synergy at an earlier stage. Our goal is to design a general methodology to facilitate knowledge discovery and produce accurate and interpretable models.

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